GoogleCapstone

"Hello everyone, and welcome to my Hospital Performance Analysis project. In this project, I used Power BI to analyze hospital appointments, patient no-shows, revenue and payment performance, and doctor performance. The main goal was to turn raw hospital data into clear insights that can support better decision-making." "Let's start with the overall hospital performance. We have a total of 200 appointments. Out of these, 46 were completed, 52 were no-shows, 51 were scheduled, and 51 were cancelled. This means that the no-show rate is around 26 percent, which represents an important operational issue that needs further investigation." "Now let's look deeper into the no-show behavior. When we segment patients by age group, the highest no-show rate appears among patients aged 60 and above, at around 41 percent. We can also see differences between insurance providers and reasons for visits. These patterns help us understand where the no-show problem is concentrated instead of looking only at the overall percentage." "Moving to the financial performance, the hospital generated approximately 551 thousand in total revenue. However, only around 173 thousand is paid revenue. Failed payments represent approximately 193 thousand, while pending payments represent around 185 thousand. This results in around 378 thousand in revenue at risk. Another important finding is that cash payments have the highest payment failure rate, at approximately 38 percent." "The final part of the dashboard focuses on doctor performance. Here, I compare the number of appointments handled by each doctor with their completion rate. This allows management to identify differences in workload and performance and understand where additional attention may be needed." "Based on these findings, I recommend focusing on four main actions. First, improve appointment reminders and confirmations to reduce no-shows. Second, investigate the reasons behind the high no-show rate among patients aged 60 and above. Third, closely monitor failed and pending payments to reduce revenue at risk. And finally, monitor doctor workload together with completion rate to support better resource allocation." "To conclude, this dashboard transforms hospital data into actionable insights. The analysis highlights three major areas: reducing no-shows, protecting revenue, and monitoring doctor performance. By continuously tracking these KPIs, hospital management can make more informed, data-driven decisions. Thank you for watching."